Designing multi-agent systems on Agentforce
When to split work across specialist agents, how orchestration routes it, and what to keep deterministic.
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Executive perspectives on the agentic enterprise.
Practical thinking for CIOs, CISOs, CRM leaders, enterprise architects, and transformation teams building and securing AI agents.
Showing 11 of 11 perspectives
A2A and MCP: connecting agents to the rest of the enterprise
How the two open protocols differ, where each fits, and how to secure the trust boundary between agents.
Request this briefingData 360 as the grounding layer for agents
Unified profiles, zero-copy access, and retrieval design that keeps answers accurate and permission-aware.
Request this briefingEnterprise RAG patterns that hold up in production
Chunking, citations, freshness, and evaluation practices for knowledge agents.
Request this briefingAgentforce security: least privilege for autonomous agents
Agent users, scoped actions, Trust Layer settings, and how to red-team an agent before launch.
Request this briefingSalesforce security and compliance in the agentic era
Why access reviews, Shield, and event monitoring matter more once agents can act on your data.
Request this briefingThe agentic SDLC
Using AI across planning, build, and test, and treating agents as versioned, tested software.
Request this briefingDevSecOps pipelines for Salesforce and AI
Automated code, metadata, secret, and prompt-security checks as release gates.
Request this briefingAgent observability: what to measure
Session tracing, task resolution, escalation, cost, and drift: the metrics that tell you an agent is working.
Request this briefingLong-horizon agents: what changes when agents work for weeks
Approval checkpoints, accountability, and how to pilot goal-driven agents safely.
Request this briefingMeasuring agent ROI beyond deflection
Building value cases on cycle time, revenue, quality, and risk, not just cases avoided.
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